Online or onsite, instructor-led live Large Language Models (LLMs) training courses demonstrate through interactive hands-on practice how to use Large Language Models for various natural language tasks.
LLMs training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Austin onsite live Large Language Models (LLMs) trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg also offers bespoke Large Language Models (LLMs) consultancy services in Austin. Our consultants have helped hundreds of clients around the world get unstuck. Our clients value our highly-personalized consulting approach and find consulting to be well-suited for complex long-term projects, short-term projects requiring niche expertise, urgent problem fixing, critical knowledge transfer, and team coaching and support. To learn more about our past consultancy engagements, see consultancy case studies.
If instead you need people for continuous projects, NobleProg can support your organisation with a full range of staff. Whether your needs are for medium-term or long-term assignments, entry-level or highly-skilled expertise, single-person or multi-person personnel, our interim staffing / staff augmentation solutions can provide you with the talent needed to complete your most challenging projects. Contact us for more information.
NobleProg -- Your Local Training Provider
Austin, TX – Regus at Dobie Center
2021 Guadalupe Street, Suite 260, Austin, United States, 78705
The venue is located in the vibrant West Campus neighborhood near the University of Texas at the Dobie Center, easily reachable by car via I‑35 or I‑35 Frontage Road and Loop 1, with on-site and street parking nearby. From Austin–Bergstrom International Airport (AUS), about 11 miles southeast, a taxi or rideshare takes around 20–25 minutes via TX‑71 West and I‑35 North. Public transit users can take Capital Metro routes to the University of Texas/Dobie Mall stop directly in front of the building, placing it within a short walk for attendees without cars.
Austin, TX - Regus - Littlefield Congress
106 E 6th St, Austin, United States, 78701
The venue is conveniently situated near I‑35 and US‑183, making it easily accessible by car, with both public and garage parking options—such as the Littlefield Garage at 508 Brazos—located within walking distance. For those using public transportation, the venue is just a short walk from the Downtown Station (CapMetro) and is served by several bus routes. Travelers arriving by air will find that Austin-Bergstrom International Airport is approximately 8 miles away, providing straightforward access to and from the venue.
This instructor-led, live training in Austin (online or onsite) is aimed at senior management professionals who wish to understand what LLMs are, explore their potential impact on business operations, and evaluate practical uses of AI tools such as ChatGPT, Microsoft Copilot, or Grok for real-world tasks like content creation, data summarization, and decision support.
By the end of this training, participants will be able to:
Understand what LLMs are and how tools like ChatGPT and Copilot function.
Use prompt techniques to get practical, reliable results from LLMs.
Evaluate real use cases such as email drafting, summarizing documents, and productivity automation.
Identify investment opportunities and strategic applications for AI adoption.
This instructor-led, live training in Austin (online or onsite) is aimed at senior management teams who wish to understand the strategic value of LLMs and enterprise AI tools. Participants will explore how to integrate these tools into high-level workflows, draft better prompts, and evaluate opportunities for increased productivity and ROI through AI adoption.
By the end of this training, participants will be able to:
Understand how LLMs function and how tools like ChatGPT and Copilot apply them.
Use prompt-based interactions to automate and accelerate tasks.
Apply AI tools to real scenarios such as email drafting, report summarization, and agreement review.
Evaluate strategic benefits, limitations, and licensing considerations for LLM adoption.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level to advanced-level AI researchers, data scientists, and developers who wish to understand, fine-tune, and implement Meta AI's Large Language Models for various NLP applications.
By the end of this training, participants will be able to:
Understand the architecture and functioning of Meta AI's Large Language Models.
Set up and fine-tune Meta AI LLMs for specific use cases.
Implement LLM-based applications such as text summarization, chatbots, and sentiment analysis.
Optimize and deploy large language models efficiently.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level AI professionals, business analysts, and technology leaders who wish to understand the principles of generative AI and the applications of LLMs in business settings. Participants will learn about transformers, prompt engineering, and ethical considerations in deploying these models for real-world solutions.
By the end of this training, participants will be able to:
Understand the underlying principles of generative AI and large language models.
Implement and fine-tune LLMs for specific business applications.
Apply prompt engineering techniques for optimal model outputs.
Recognize ethical considerations and manage risks in LLM deployment.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level AI professionals and ethicists, data scientists and engineers, and policy makers and stakeholders who wish to understand and navigate the ethical landscape of LLMs.
By the end of this training, participants will be able to:
Identify ethical issues and challenges associated with LLMs.
Apply ethical frameworks and principles to LLM deployment.
Assess the societal impact of LLMs and mitigate potential risks.
Develop strategies for responsible AI development and usage.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level NLP practitioners and data scientists, content creators and translators, and global businesses who wish to use LLMs for language translation and creating multilingual content.
By the end of this training, participants will be able to:
Understand the principles of cross-lingual learning and translation with LLMs.
Implement LLMs for translating content between various languages.
Create and manage multilingual datasets for training LLMs.
Develop strategies for maintaining consistency and quality in translation.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level financial analysts, data scientists, and investment professionals who wish to leverage LLMs for financial market analysis and prediction.
By the end of this training, participants will be able to:
Understand the application of LLMs in financial market analysis.
Use LLMs to process financial news, reports, and data for market insights.
Develop predictive models for stock prices, market trends, and economic indicators.
Integrate LLM insights into investment decision-making processes.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level environmental scientists and researchers, data analysts, and policy makers and environmental advocates who wish to use LLMs for environmental modeling and analysis.
By the end of this training, participants will be able to:
Understand the application of LLMs in environmental science.
Utilize LLMs to analyze and model environmental data.
Interpret LLM outputs for environmental impact assessments.
Communicate findings effectively to inform policy and conservation efforts.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level VR and AR developers, game designers, and AI engineers who wish to incorporate LLMs into VR and AR applications to create more engaging and responsive environments.
By the end of this training, participants will be able to:
Understand the role of LLMs in creating immersive VR and AR experiences.
Develop VR and AR applications that utilize LLMs for interactive dialogues and content creation.
Integrate LLMs with VR and AR development tools for enhanced user engagement.
Apply best practices for designing AI-driven narratives and interactions in virtual spaces.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level data scientists, machine learning engineers, and software developers who wish to apply Large Language Models (LLMs) to multimodal data for advanced AI applications.
By the end of this training, participants will be able to:
Understand the principles of multimodal learning with LLMs.
Implement LLMs to process and analyze text, image, and audio data.
Develop applications that leverage the strengths of multimodal data integration.
Evaluate the performance of multimodal LLM systems.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level cybersecurity professionals and data scientists who wish to utilize LLMs for enhancing cybersecurity measures and threat intelligence.
By the end of this training, participants will be able to:
Understand the role of LLMs in cybersecurity.
Implement LLMs for threat detection and analysis.
Utilize LLMs for security automation and response.
Integrate LLMs with existing security infrastructure.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level data scientists and business analysts who wish to utilize large language models (LLMs) to forecast trends and behaviors in various industries.
By the end of this training, participants will be able to:
Understand the fundamentals of LLMs and their role in predictive analytics.
Implement LLMs to analyze and forecast data in various industries.
Evaluate the effectiveness of predictive models using LLMs.
Integrate LLMs with existing data processing pipelines.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level data scientists who wish to gain a comprehensive understanding and practical skills in both Large Language Models (LLMs) and Reinforcement Learning (RL).
By the end of this training, participants will be able to:
Understand the components and functionality of transformer models.
Optimize and fine-tune LLMs for specific tasks and applications.
Understand the core principles and methodologies of reinforcement learning.
Learn how reinforcement learning techniques can enhance the performance of LLMs.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level content creators, marketers, and educational technologists who wish to harness the power of LLMs for generating high-quality, diverse, and engaging content across various domains.
By the end of this training, participants will be able to:
Understand the capabilities of LLMs and their application in content generation.
Set up and use LLMs for generating various types of content.
Apply best practices for prompting and fine-tuning LLMs to produce desired outputs.
Evaluate the quality of AI-generated content and refine it for specific audiences.
Explore advanced techniques for creative and multi-modal content generation with LLMs.
This instructor-led, live training in Austin (online or onsite) is aimed at educators, EdTech professionals, and researchers with varying levels of experience and expertise who wish to leverage LLMs for creating personalized educational experiences.
By the end of this training, participants will be able to:
Understand the architecture and capabilities of LLMs.
Identify opportunities for personalization in educational content using LLMs.
Design adaptive learning platforms that utilize LLMs for content personalization.
Implement LLM-driven strategies for enhancing student engagement and learning outcomes.
Evaluate the effectiveness of LLMs in educational settings and make data-driven decisions for
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level ML practitioners and AI developers who wish to fine-tune and deploy open-weight models like LLaMA, Mistral, and Qwen for specific business or internal applications.
By the end of this training, participants will be able to:
Understand the ecosystem and differences between open-source LLMs.
Prepare datasets and fine-tuning configurations for models like LLaMA, Mistral, and Qwen.
Execute fine-tuning pipelines using Hugging Face Transformers and PEFT.
Evaluate, save, and deploy fine-tuned models in secure environments.
This instructor-led, live training in Austin (online or onsite) is aimed at beginner-level to intermediate-level software developers and data scientists who wish to implement LLMs in speech recognition and synthesis systems.
By the end of this training, participants will be able to:
Understand the role of LLMs in speech technologies.
Implement LLMs for accurate speech recognition and natural-sounding speech synthesis.
Integrate LLMs with speech recognition engines and speech synthesizers.
Evaluate and improve the performance of speech systems using LLMs.
Stay informed about current trends and future directions in speech technologies.
This instructor-led, live training in Austin (online or onsite) is aimed at beginner-level to intermediate-level customer support and IT professionals who wish to implement LLMs to create responsive and intelligent customer support chatbots.
By the end of this training, participants will be able to:
Understand the fundamentals and architecture of Large Language Models (LLMs).
Design and integrate LLMs into customer support systems.
Enhance the responsiveness and user experience of chatbots.
Address ethical considerations and ensure compliance with industry standards.
Deploy and maintain an LLM-based chatbot for real-world applications.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level data scientists and AI engineers who wish to fine-tune large language models more affordably and efficiently using methods like LoRA, Adapter Tuning, and Prefix Tuning.
By the end of this training, participants will be able to:
Understand the theory behind parameter-efficient fine-tuning approaches.
Implement LoRA, Adapter Tuning, and Prefix Tuning using Hugging Face PEFT.
Compare performance and cost trade-offs of PEFT methods vs. full fine-tuning.
Deploy and scale fine-tuned LLMs with reduced compute and storage requirements.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level to advanced-level machine learning engineers, AI developers, and data scientists who wish to learn how to use QLoRA to efficiently fine-tune large models for specific tasks and customizations.
By the end of this training, participants will be able to:
Understand the theory behind QLoRA and quantization techniques for LLMs.
Implement QLoRA in fine-tuning large language models for domain-specific applications.
Optimize fine-tuning performance on limited computational resources using quantization.
Deploy and evaluate fine-tuned models in real-world applications efficiently.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level data and marketing professionals who wish to apply LLMs to analyze and interpret public sentiment from various text sources such as social media posts, product reviews, and customer feedback.
By the end of this training, participants will be able to:
Understand the principles of sentiment analysis and its application using LLMs.
Preprocess and prepare datasets for sentiment analysis.
Train and fine-tune LLMs to accurately reflect sentiment in text.
Analyze sentiment in real-time from social media and other text sources.
Integrate sentiment analysis findings into business strategies and decision-making processes.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level software developers and technical writers who wish to leverage LLMs to streamline their coding workflow and create detailed, comprehensive documentation.
By the end of this training, participants will be able to:
Understand the role of LLMs in automating code generation and software documentation.
Utilize LLMs to create accurate and efficient code snippets and documentation.
Integrate LLMs into their software development lifecycle for enhanced productivity.
Maintain high-quality documentation standards using automated tools.
Address ethical considerations and best practices for using AI in software development.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level business professionals and data analysts who wish to harness the power of LLMs for extracting business insights.
By the end of this training, participants will be able to:
Understand the fundamentals and applications of LLMs in the context of business intelligence.
Apply LLMs to analyze large datasets and extract meaningful insights.
Integrate LLM-driven analytics into strategic business decision-making processes.
Evaluate the ethical considerations and best practices for using LLMs in business.
Anticipate future trends in AI and prepare for the evolving landscape of business intelligence.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level to advanced-level developers and data scientists who wish to master LlamaIndex for developing innovative LLM-powered applications.
By the end of this training, participants will be able to:
Set up and configure LlamaIndex for use with LLMs.
Index and query custom datasets using LlamaIndex to enhance LLM functionality.
Design and develop sophisticated applications that utilize LlamaIndex and LLMs.
Understand and apply best practices for working with LLMs and LlamaIndex.
Navigate the ethical considerations involved in deploying LLM-powered applications.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level AI researchers, machine learning professionals, and data scientists who wish to use LlamaIndex to enhance the capabilities of AI models, making them more accurate and reliable for various applications.
By the end of this training, participants will be able to:
Understand the principles and components of LlamaIndex.
Ingest and structure data for use with LLMs.
Implement context augmentation to improve AI model performance.
Integrate LlamaIndex into existing AI systems and workflows.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level professionals who wish to leverage the power of prompt engineering and few-shot learning to optimize LLM performance for real-world applications.
By the end of this training, participants will be able to:
Understand the principles of prompt engineering and few-shot learning.
Design effective prompts for various NLP tasks.
Leverage few-shot techniques to adapt LLMs with minimal data.
Optimize LLM performance for practical applications.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level public sector professionals who wish to use Gemini to generate high-quality content, assist with research, and improve productivity through more advanced AI interactions.
By the end of this training, participants will be able to:
Craft more effective and tailored prompts for specific use cases.
Generate original and creative content using Gemini.
Summarize and compare complex information with precision.
Use Gemini for brainstorming, planning, and organizing ideas efficiently.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level researchers, analysts, and knowledge workers who want to leverage Claude AI for processing large amounts of data, synthesizing information, and automating research tasks.
By the end of this training, participants will be able to:
Use Claude AI for literature reviews and research synthesis.
Summarize reports, research papers, and long-form documents.
Extract key insights and trends from structured and unstructured data.
Integrate Claude AI into research and knowledge management workflows.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level professionals who wish to deepen their understanding of conversational agents and apply LangChain to real-world use cases.
By the end of this training, participants will be able to:
Understand the fundamentals of LangChain and its application in building conversational agents.
Develop and deploy conversational agents using LangChain.
Integrate conversational agents with APIs and external services.
Apply Natural Language Processing (NLP) techniques to improve the performance of conversational agents.
This instructor-led, live training in Austin (online or onsite) is aimed at beginner-level to intermediate-level content creators, writers, and marketers who want to leverage Claude AI for content generation, editing, and summarization to enhance blogs, reports, and marketing materials.
By the end of this training, participants will be able to:
Use Claude AI for content brainstorming and idea expansion.
Enhance writing with AI-assisted editing and proofreading.
Generate summaries for long-form content and reports.
Automate marketing copy creation for different platforms.
This instructor-led, live training in Austin (online or onsite) is aimed at advanced-level professionals who wish to fine-tune and customize AI models on Ollama for enhanced performance and domain-specific applications.
By the end of this training, participants will be able to:
Set up an efficient environment for fine-tuning AI models on Ollama.
Prepare datasets for supervised fine-tuning and reinforcement learning.
Optimize AI models for performance, accuracy, and efficiency.
Deploy customized models in production environments.
Evaluate model improvements and ensure robustness.
This instructor-led, live training in Austin (online or onsite) is aimed at beginner-level to intermediate-level data analysts and business professionals who wish to perform complex data analysis tasks more intuitively across various industries using Google Gemini AI.
By the end of this training, participants will be able to:
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level developers who wish to learn how to use generative AI with LLMs for various tasks and domains.
By the end of this training, participants will be able to:
Explain what generative AI is and how it works.
Describe the transformer architecture that powers LLMs.
Use empirical scaling laws to optimize LLMs for different tasks and constraints.
Apply state-of-the-art tools and methods to train, fine-tune, and deploy LLMs.
Discuss the opportunities and risks of generative AI for society and business.
LLMs and autonomous agent frameworks like AutoGen and CrewAI are redefining how DevOps teams automate tasks such as change tracking, test generation, and alert triage by simulating human-like collaboration and decision-making.
This instructor-led, live training (online or onsite) is aimed at advanced-level engineers who wish to design and implement DevOps automation workflows powered by large language models (LLMs) and multi-agent systems.
By the end of this training, participants will be able to:
Integrate LLM-based agents into CI/CD workflows for smart automation.
Automate test generation, commit analysis, and change summaries using agents.
Coordinate multiple agents for triaging alerts, generating responses, and providing DevOps recommendations.
Build secure and maintainable agent-powered workflows using open-source frameworks.
Format of the Course
Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
This instructor-led, live training in Austin (online or onsite) is aimed at developers and IT professionals of all skill levels who wish to automate tasks and processes using AI without writing extensive code.
By the end of this training, participants will be able to:
Design and implement complex workflows using n8n's visual programming interface.
Integrate AI capabilities into workflows using LangChain.
Build custom chatbots and virtual assistants for various use cases.
Perform advanced data analysis and processing with AI agents.
This instructor-led, live training in Austin (online or onsite) is aimed at advanced-level professionals who wish to implement secure and efficient AI-driven workflows using Ollama.
By the end of this training, participants will be able to:
Deploy and configure Ollama for private AI processing.
Integrate AI models into secure enterprise workflows.
Optimize AI performance while maintaining data privacy.
Automate business processes with on-premise AI capabilities.
Ensure compliance with enterprise security and governance policies.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level to advanced-level AI developers, architects, and product managers who wish to identify and mitigate risks associated with LLM-powered applications, including prompt injection, data leakage, and unfiltered output, while incorporating security controls like input validation, human-in-the-loop oversight, and output guardrails.
By the end of this training, participants will be able to:
Understand the core vulnerabilities of LLM-based systems.
Apply secure design principles to LLM app architecture.
Use tools such as Guardrails AI and LangChain for validation, filtering, and safety.
Integrate techniques like sandboxing, red teaming, and human-in-the-loop review into production-grade pipelines.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level software developers and AI engineers who wish to integrate Claude AI into their applications, build AI-powered chatbots, and enhance software functionality with AI-driven automation.
By the end of this training, participants will be able to:
Use the Claude AI API to integrate AI into applications.
Develop AI-driven chatbots and virtual assistants.
Enhance applications with AI-powered automation and NLP.
Optimize and fine-tune Claude AI models for different use cases.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level content creators who wish to utilize Google Gemini AI to enhance their content quality and efficiency.
By the end of this training, participants will be able to:
Understand the role of AI in content creation.
Set up and use Google Gemini AI to generate and optimize content.
Apply text-to-text transformations to produce creative and original content.
Implement SEO strategies using AI-driven insights.
Analyze content performance and adapt strategies using Gemini AI.
This instructor-led, live training in Austin (online or onsite) is aimed at beginner-level professionals who wish to integrate Claude AI into their daily workflows to improve efficiency and automation.
By the end of this training, participants will be able to:
Use Claude AI for automating repetitive tasks and streamlining workflows.
Enhance personal and team productivity using AI-powered automation.
Integrate Claude AI with existing business tools and platforms.
Optimize AI-driven decision-making and task management.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level professionals who wish to deploy, optimize, and integrate LLMs using Ollama.
By the end of this training, participants will be able to:
Set up and deploy LLMs using Ollama.
Optimize AI models for performance and efficiency.
Leverage GPU acceleration for improved inference speeds.
Integrate Ollama into workflows and applications.
Monitor and maintain AI model performance over time.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level to advanced-level professionals who wish to customize pre-trained models for specific tasks and datasets.
By the end of this training, participants will be able to:
Understand the principles of fine-tuning and its applications.
Prepare datasets for fine-tuning pre-trained models.
Fine-tune large language models (LLMs) for NLP tasks.
Optimize model performance and address common challenges.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level customer service professionals who wish to implement Google Gemini AI in their customer service operations.
By the end of this training, participants will be able to:
Understand the impact of AI on customer service.
Set up Google Gemini AI to automate and personalize customer interactions.
Utilize text-to-text and image-to-text transformations to improve service efficiency.
Develop AI-driven strategies for real-time customer feedback analysis.
Explore advanced features to create a seamless customer service experience.
This instructor-led, live training in Austin (online or onsite) is aimed at beginner-level to intermediate-level developers and software engineers who wish to learn the core concepts and architecture of LangChain and gain the practical skills for building AI-powered applications.
By the end of this training, participants will be able to:
Grasp the fundamental principles of LangChain.
Set up and configure the LangChain environment.
Understand the architecture and how LangChain interacts with large language models (LLMs).
LLMs for Code Understanding, Refactoring, and Documentation is a technical course focused on applying large language models (LLMs) to improve code quality, reduce technical debt, and automate documentation tasks across software teams.
This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level software professionals who wish to use LLMs such as GPT to analyze, refactor, and document complex or legacy codebases more effectively.
By the end of this training, participants will be able to:
Use LLMs to explain code, dependencies, and logic in unfamiliar repositories.
Identify and refactor anti-patterns and improve code readability.
Automatically generate and maintain in-line comments, README files, and API documentation.
Integrate LLM-driven insights into existing CI/CD and review workflows.
Format of the Course
Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level data scientists, AI developers, and AI enthusiasts who wish to use LLMs to perform various NLP tasks and create novel and diverse content for different purposes.
By the end of this training, participants will be able to:
Establish a development environment with LLMs and essential tools.
Expertly perform NLU and NLI tasks with LLMs.
Extract, infer, and utilize knowledge graphs effectively.
Generate and manage dialogues using LLMs for conversational applications.
Evaluate content quality and diversity generated by LLMs and generative AI.
Apply ethical principles, ensuring fairness and responsible use of LLMs.
This instructor-led, live training in Austin (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to integrate AI functionalities into their applications using Google Gemini AI.
By the end of this training, participants will be able to:
Understand the fundamentals of large language models.
Set up and use Google Gemini AI for various AI tasks.
Implement text-to-text and image-to-text transformations.
Build basic AI-driven applications.
Explore advanced features and customization options in Google Gemini AI.
This instructor-led, live training in Austin (online or onsite) is aimed at beginner-level business professionals, customer support teams, and tech enthusiasts who wish to understand the fundamentals of Claude AI and leverage it for business applications.
By the end of this training, participants will be able to:
Understand Claude AI’s capabilities and use cases.
Set up and interact with Claude AI effectively.
Automate business workflows with conversational AI.
Enhance customer engagement and support using AI-driven solutions.
This instructor-led, live training in Austin (online or onsite) is aimed at intermediate-level developers and software engineers who wish to build AI-powered applications using the LangChain framework.
By the end of this training, participants will be able to:
Understand the fundamentals of LangChain and its components.
Integrate LangChain with large language models (LLMs) like GPT-4.
Build modular AI applications using LangChain.
Troubleshoot common issues in LangChain applications.
This instructor-led, live training in Austin (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to use Large Language Models for various natural language tasks.
By the end of this training, participants will be able to:
Set up a development environment that includes a popular LLM.
Create a basic LLM and fine-tune it on a custom dataset.
Use LLMs for different natural language tasks such as text summarization, question answering, text generation, and more.
Debug and evaluate LLMs using tools such as TensorBoard, PyTorch Lightning, and Hugging Face Datasets.
This instructor-led, live training in Austin (online or onsite) is aimed at beginner-level professionals who wish to install, configure, and use Ollama for running AI models on their local machines.
By the end of this training, participants will be able to:
Understand the fundamentals of Ollama and its capabilities.
Set up Ollama for running local AI models.
Deploy and interact with LLMs using Ollama.
Optimize performance and resource usage for AI workloads.
Explore use cases for local AI deployment in various industries.
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Testimonials (1)
prompts engineering part
Michal - GE HealthCare
Course - Generative AI with Large Language Models (LLMs)
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